1
|
Brognara L. Gait Assessment Using Smartphone Applications in Older Adults: A Scoping Review. Geriatrics (Basel) 2024; 9:95. [PMID: 39051259 PMCID: PMC11270307 DOI: 10.3390/geriatrics9040095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2024] [Revised: 07/15/2024] [Accepted: 07/17/2024] [Indexed: 07/27/2024] Open
Abstract
Spatiotemporal parameters such as gait velocity and stride length are simple indicators of functional status and can be used to predict major adverse outcomes in older adults. A smartphone can be used for gait analysis by providing spatiotemporal parameters useful for improving the diagnosis and rehabilitation processes in frail people. The aim of this study was to review articles published in the last 20 years (from 2004 to 2024) concerning the application of smartphones to assess the spatiotemporal parameters of gait in older adults. This systematic review was performed in line with Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA), and original articles were identified by searching seven electronic databases: SciVerse (ScienceDirect), Excerpta Medica Database (EMBASE), Medline, Scopus, PubMed, Web of Science and the Cochrane Library. Studies were rigorously screened using the inclusion criteria of smartphones and mobile apps, older adults and spatiotemporal gait parameters, and results were narratively synthesized. Seventy-three articles were initially identified while searching the scientific literature regarding this topic. Eleven articles were selected and included in this review. Analysis of these studies covered information about gait assessment using mobile apps recorded in 723 older adults and 164 control cases. Analysis of data related to the application of smartphones to assess spatiotemporal parameters of gait in older adults showed moderate-to-excellent test-retest reliability and validity (ICCs around 0.9) of gait speed, the most common parameter reported. Additionally, gait speeds recorded with mobile apps showed excellent agreement when compared to gold standard systems. Smartphones and mobile apps are useful, non-invasive, low-cost and objective tools that are being extensively used to perform gait analysis in older adults. Smartphones and mobile apps can reliably identify spatiotemporal parameters related to adverse outcomes, such as a slow gait speed, as predictors and outcomes in clinical practice and research involving older adults.
Collapse
Affiliation(s)
- Lorenzo Brognara
- Department of Biomedical and Neuromotor Sciences (DIBINEM), University of Bologna, 40123 Bologna, Italy
| |
Collapse
|
2
|
Bougea A. Digital biomarkers in Parkinson's disease. Adv Clin Chem 2024; 123:221-253. [PMID: 39181623 DOI: 10.1016/bs.acc.2024.06.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/27/2024]
Abstract
Digital biomarker (DB) assessments provide objective measures of daily life tasks and thus hold promise to improve diagnosis and monitoring of Parkinson's disease (PD) patients especially those with advanced stages. Data from DB studies can be used in advanced analytics such as Artificial Intelligence and Machine Learning to improve monitoring, treatment and outcomes. Although early development of inertial sensors as accelerometers and gyroscopes in smartphones provided encouraging results, the use of DB remains limited due to lack of standards, harmonization and consensus for analytical as well as clinical validation. Accordingly, a number of clinical trials have been developed to evaluate the performance of DB vs traditional assessment tools with the goal of monitoring disease progression, improving quality of life and outcomes. Herein, we update current evidence on the use of DB in PD and highlight potential benefits and limitations and provide suggestions for future research study.
Collapse
Affiliation(s)
- Anastasia Bougea
- Department of Neurology, Medical School, Aeginition Hospital, National and Kapodistrian University of Athens, Athens, Greece.
| |
Collapse
|
3
|
Bruni F, Mancuso V, Stramba-Badiale C, Stramba-Badiale M, Riva G, Goulene K, Cipresso P, Pedroli E. Beyond traditional training: Integrating data from semi-immersive VR dual-task intervention in Parkinsonian Syndromes. A study protocol. PLoS One 2024; 19:e0294199. [PMID: 38300977 PMCID: PMC10833523 DOI: 10.1371/journal.pone.0294199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2023] [Accepted: 10/22/2023] [Indexed: 02/03/2024] Open
Abstract
Completing cognitive and motor tasks simultaneously requires a high level of cognitive control in terms of executive processes and attentional abilities. Most of the daily activities require a dual-task performance. While walking, for example, it may be necessary to adapt gait to obstacles of the environment or simply participate in a conversation; all these activities involve more than one ability at the same time. This parallel performance may be critical in the cognitive or motor load, especially for patients with neurological diseases such as Parkinsonian Syndromes. Patients are often characterized by a crucial impairment in performing both tasks concurrently, showing a decrease in attention skills and executive functions, thus leading to increased negative outcomes. In this scenario, the accurate assessment of the components involved in dual-task performance is crucial, and providing an early specific training program appears to be essential. The objective of this protocol is to assess cognitive and motor components involved in dual-task performance and create a training program based on ecological activities focusing on executive and motor functions. Thus, we will employ Virtual Reality to provide semi-immersive, multisensory, ecological, standardized, and realistic experiences for rehabilitative purposes in patients with Parkinsonian Syndromes, considering its high prevalence in aging and the incidence of motor and cognitive dysfunctions in this population. Moreover, we propose to integrate the great amount of different data provided by dual-task and Virtual Reality system, using machine learning techniques. These integrations may increase the treatment's reliability in terms of better prognostic indexes and individualized training.
Collapse
Affiliation(s)
| | | | - Chiara Stramba-Badiale
- Applied Technology for Neuropsychology Lab, IRCCS Istituto Auxologico Italiano, Milan, Italy
| | - Marco Stramba-Badiale
- Department of Geriatrics and Cardiovascular Medicine, IRCCS Istituto Auxologico Italiano, Milan, Italy
| | - Giuseppe Riva
- Applied Technology for Neuropsychology Lab, IRCCS Istituto Auxologico Italiano, Milan, Italy
- Human Technology Lab, Catholic University of the Sacred Heart, Milan, Italy
| | - Karine Goulene
- Department of Geriatrics and Cardiovascular Medicine, IRCCS Istituto Auxologico Italiano, Milan, Italy
| | - Pietro Cipresso
- Department of Psychology, University of Turin, Turin, Italy
- Istituto Auxologico Italiano, IRCCS, Unit of Neurology and Neurorehabilitation, San Giuseppe Hospital Piancavallo, Verbania, Italy
| | - Elisa Pedroli
- Faculty of Psychology, eCampus University, Novedrate, Italy
- Department of Geriatrics and Cardiovascular Medicine, IRCCS Istituto Auxologico Italiano, Milan, Italy
| |
Collapse
|
4
|
Moreau C, Rouaud T, Grabli D, Benatru I, Remy P, Marques AR, Drapier S, Mariani LL, Roze E, Devos D, Dupont G, Bereau M, Fabbri M. Overview on wearable sensors for the management of Parkinson's disease. NPJ Parkinsons Dis 2023; 9:153. [PMID: 37919332 PMCID: PMC10622581 DOI: 10.1038/s41531-023-00585-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 10/02/2023] [Indexed: 11/04/2023] Open
Abstract
Parkinson's disease (PD) is affecting about 1.2 million patients in Europe with a prevalence that is expected to have an exponential increment, in the next decades. This epidemiological evolution will be challenged by the low number of neurologists able to deliver expert care for PD. As PD is better recognized, there is an increasing demand from patients for rigorous control of their symptoms and for therapeutic education. In addition, the highly variable nature of symtoms between patients and the fluctuations within the same patient requires innovative tools to help doctors and patients monitor the disease in their usual living environment and adapt treatment in a more relevant way. Nowadays, there are various body-worn sensors (BWS) proposed to monitor parkinsonian clinical features, such as motor fluctuations, dyskinesia, tremor, bradykinesia, freezing of gait (FoG) or gait disturbances. BWS have been used as add-on tool for patients' management or research purpose. Here, we propose a practical anthology, summarizing the characteristics of the most used BWS for PD patients in Europe, focusing on their role as tools to improve treatment management. Consideration regarding the use of technology to monitor non-motor features is also included. BWS obviously offer new opportunities for improving management strategy in PD but their precise scope of use in daily routine care should be clarified.
Collapse
Affiliation(s)
- Caroline Moreau
- Department of Neurology, Parkinson's disease expert Center, Lille University, INSERM UMRS_1172, University Hospital Center, Lille, France
- The French Ns-Park Network, Paris, France
| | - Tiphaine Rouaud
- The French Ns-Park Network, Paris, France
- CHU Nantes, Centre Expert Parkinson, Department of Neurology, Nantes, F-44093, France
| | - David Grabli
- The French Ns-Park Network, Paris, France
- Assistance Publique Hôpitaux de Paris, Department of Neurology, CIC Neurosciences, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
- Sorbonne University, Paris Brain Institute - ICM, Inserm, CNRS, Paris, France
| | - Isabelle Benatru
- The French Ns-Park Network, Paris, France
- Department of Neurology, University Hospital of Poitiers, Poitiers, France
- INSERM, CHU de Poitiers, University of Poitiers, Centre d'Investigation Clinique CIC1402, Poitiers, France
| | - Philippe Remy
- The French Ns-Park Network, Paris, France
- Centre Expert Parkinson, NS-Park/FCRIN Network, CHU Henri Mondor, AP-HP, Equipe NPI, IMRB, INSERM et Faculté de Santé UPE-C, Créteil, FranceService de neurologie, hôpital Henri-Mondor, AP-HP, Créteil, France
| | - Ana-Raquel Marques
- The French Ns-Park Network, Paris, France
- Université Clermont Auvergne, CNRS, Clermont Auvergne INP, Institut Pascal, Clermont-Ferrand University Hospital, Neurology department, Clermont-Ferrand, France
| | - Sophie Drapier
- The French Ns-Park Network, Paris, France
- Pontchaillou University Hospital, Department of Neurology, CIC INSERM 1414, Rennes, France
| | - Louise-Laure Mariani
- The French Ns-Park Network, Paris, France
- Assistance Publique Hôpitaux de Paris, Department of Neurology, CIC Neurosciences, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
- Sorbonne University, Paris Brain Institute - ICM, Inserm, CNRS, Paris, France
| | - Emmanuel Roze
- The French Ns-Park Network, Paris, France
- Assistance Publique Hôpitaux de Paris, Department of Neurology, CIC Neurosciences, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
- Sorbonne University, Paris Brain Institute - ICM, Inserm, CNRS, Paris, France
| | - David Devos
- The French Ns-Park Network, Paris, France
- Parkinson's Disease Centre of Excellence, Department of Medical Pharmacology, Univ. Lille, INSERM; CHU Lille, U1172 - Degenerative & Vascular Cognitive Disorders, LICEND, NS-Park Network, F-59000, Lille, France
| | - Gwendoline Dupont
- The French Ns-Park Network, Paris, France
- Centre hospitalier universitaire François Mitterrand, Département de Neurologie, Université de Bourgogne, Dijon, France
| | - Matthieu Bereau
- The French Ns-Park Network, Paris, France
- Service de neurologie, université de Franche-Comté, CHRU de Besançon, 25030, Besançon, France
| | - Margherita Fabbri
- The French Ns-Park Network, Paris, France.
- Department of Neurosciences, Clinical Investigation Center CIC 1436, Parkinson Toulouse Expert Centre, NS-Park/FCRIN Network and NeuroToul COEN Center, Toulouse University Hospital, INSERM, University of Toulouse 3, Toulouse, France.
| |
Collapse
|
5
|
Mostovov A, Jacobs D, Farid L, Dhellin P, Baille G. Test-retest reliability of the six-minute walking distance measurements using FeetMe insoles by completely unassisted healthy adults in their homes. PLOS DIGITAL HEALTH 2023; 2:e0000262. [PMID: 37992015 PMCID: PMC10664940 DOI: 10.1371/journal.pdig.0000262] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Accepted: 10/16/2023] [Indexed: 11/24/2023]
Abstract
Wearable technology provides an opportunity for new ways of monitoring patient gait remotely, through at-home self-administered six-minute walk tests (6MWTs). The purpose of this study was to evaluate the test-retest reliability of FeetMe insoles, a wearable gait assessment device, for measuring the six-minute walking distance (6MWD) during tests conducted with a one-week interval by completely unassisted healthy adults in their homes. Participants (n = 21) performed two 6MWTs at home while wearing the FeetMe insoles, and two 6MWTs at hospital while wearing FeetMe insoles and being assessed by a rater. All assessments were performed with a one-week interval between tests, no assistance was provided to the participants at home. The agreement between the 6MWD measurements made at baseline and at Week 1 was good for all test configurations and was highest for the at-home FeetMe measurements, with an intraclass correlation coefficient (ICC) of 0.95, standard error of the measurement (SEM) of 15.02 m and coefficient of variation (CV) of 3.33%, compared to ICCs of 0.79 and 0.78, SEMs of 25.65 and 26.65 and CVs of 6.24% and 6.10% for the rater and FeetMe measurements at hospital, respectively. Our work demonstrates that the FeetMe system could provide a reliable solution allowing individuals to self-administer 6MWTs independently at home.
Collapse
Affiliation(s)
| | | | - Leila Farid
- FeetMe SAS, 157 bd. MacDonald, Paris, France
| | | | - Guillaume Baille
- Neurology department, Delafontaine Hospital Center, Saint-Denis, France
| |
Collapse
|
6
|
Ciceri T, Malerba G, Gatti A, Diella E, Peruzzo D, Biffi E, Casartelli L. Context expectation influences the gait pattern biomechanics. Sci Rep 2023; 13:5644. [PMID: 37024572 PMCID: PMC10079826 DOI: 10.1038/s41598-023-32665-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 03/30/2023] [Indexed: 04/08/2023] Open
Abstract
Beyond classical aspects related to locomotion (biomechanics), it has been hypothesized that walking pattern is influenced by a combination of distinct computations including online sensory/perceptual sampling and the processing of expectations (neuromechanics). Here, we aimed to explore the potential impact of contrasting scenarios ("risky and potentially dangerous" scenario; "safe and comfortable" scenario) on walking pattern in a group of healthy young adults. Firstly, and consistently with previous literature, we confirmed that the scenario influences gait pattern when it is recalled concurrently to participants' walking activity (motor interference). More intriguingly, our main result showed that participants' gait pattern is also influenced by the contextual scenario when it is evoked only before the start of walking activity (motor expectation). This condition was designed to test the impact of expectations (risky scenario vs. safe scenario) on gait pattern, and the stimulation that preceded walking activity served as prior. Noteworthy, we combined statistical and machine learning (Support-Vector Machine classifier) approaches to stratify distinct levels of analyses that explored the multi-facets architecture of walking. In a nutshell, our combined statistical and machine learning analyses converge in suggesting that walking before steps is not just a paradox.
Collapse
Affiliation(s)
- Tommaso Ciceri
- Department of Information Engineering, University of Padova, Padua, PD, Italy
- Neuroimaging Lab, Scientific Institute IRCCS E. Medea, Bosisio Parini, LC, Italy
| | - Giorgia Malerba
- Bioengineering Lab, Scientific Institute IRCCS E. Medea, Bosisio Parini, LC, Italy
| | - Alice Gatti
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, MI, Italy
| | - Eleonora Diella
- Bioengineering Lab, Scientific Institute IRCCS E. Medea, Bosisio Parini, LC, Italy
| | - Denis Peruzzo
- Neuroimaging Lab, Scientific Institute IRCCS E. Medea, Bosisio Parini, LC, Italy
| | - Emilia Biffi
- Bioengineering Lab, Scientific Institute IRCCS E. Medea, Bosisio Parini, LC, Italy.
| | - Luca Casartelli
- Theoretical and Cognitive Neuroscience Unit, Scientific Institute IRCCS E. Medea, Bosisio Parini, LC, Italy
| |
Collapse
|
7
|
Reneaud N, Zory R, Guérin O, Thomas L, Colson SS, Gerus P, Chorin F. Validation of 3D Knee Kinematics during Gait on Treadmill with an Instrumented Knee Brace. SENSORS (BASEL, SWITZERLAND) 2023; 23:1812. [PMID: 36850411 PMCID: PMC9968020 DOI: 10.3390/s23041812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 01/27/2023] [Accepted: 01/31/2023] [Indexed: 06/18/2023]
Abstract
To test a novel instrumented knee brace intended for use as a rehabilitation system, based on inertial measurement units (IMU) to monitor home-based exercises, the device was compared to the gold standard of motion analysis. The purpose was to validate a new calibration method through functional tasks and assessed the value of adding magnetometers for motion analysis. Thirteen healthy young adults performed a 60-second gait test at a comfortable walking speed on a treadmill. Knee kinematics were captured simultaneously, using the instrumented knee brace and an optoelectronic camera system (OCS). The intraclass correlation coefficient (ICC) showed excellent reliability for the three axes of rotation with and without magnetometers, with values ranging between 0.900 and 0.972. Pearson's r coefficient showed good to excellent correlation for the three axes, with the root mean square error (RMSE) under 3° with the IMUs and slightly higher with the magnetometers. The instrumented knee brace obtained certain clinical parameters, as did the OCS. The instrumented knee brace seems to be a valid tool to assess ambulatory knee kinematics, with an RMSE of <3°, which is sufficient for clinical interpretations. Indeed, this portable system can obtain certain clinical parameters just as well as the gold standard of motion analysis. However, the addition of magnetometers showed no significant advantage in terms of enhancing accuracy.
Collapse
Affiliation(s)
- Nicolas Reneaud
- Université Côte d’Azur, LAMHESS, 06205 Nice, France
- Ted Orthopedics, 37 Rue Guibal, 13003 Marseille, France
- Université Côte d’Azur, CHU, 06000 Nice, France
| | - Raphaël Zory
- Université Côte d’Azur, LAMHESS, 06205 Nice, France
- Institut Universitaire de France, 75231 Paris, France
| | - Olivier Guérin
- Université Côte d’Azur, CNRS, INSERM, IRCAN, 06107 Nice, France
| | - Luc Thomas
- Ted Orthopedics, 37 Rue Guibal, 13003 Marseille, France
| | | | | | - Frédéric Chorin
- Université Côte d’Azur, LAMHESS, 06205 Nice, France
- Université Côte d’Azur, CHU, 06000 Nice, France
| |
Collapse
|
8
|
Parati M, Gallotta M, Muletti M, Pirola A, Bellafà A, De Maria B, Ferrante S. Validation of Pressure-Sensing Insoles in Patients with Parkinson's Disease during Overground Walking in Single and Cognitive Dual-Task Conditions. SENSORS (BASEL, SWITZERLAND) 2022; 22:6392. [PMID: 36080851 PMCID: PMC9460700 DOI: 10.3390/s22176392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 07/23/2022] [Accepted: 08/11/2022] [Indexed: 06/15/2023]
Abstract
There is a need for unobtrusive and valid tools to collect gait parameters in patients with Parkinson's disease (PD). The novel promising tools are pressure-sensing insoles connected to a smartphone app; however, few studies investigated their measurement properties during simple or challenging conditions in PD patients. This study aimed to examine the validity and reliability of gait parameters computed by pressure-sensing insoles (FeetMe® insoles, Paris, France). Twenty-five PD patients (21 males, mean age: 69 (7) years) completed two walking assessment sessions. In each session, participants walked on an electronic pressure-sensitive walkway (GaitRite®, CIR System Inc., Franklin, NJ, USA) without other additional instructions (i.e., single-task condition) and while performing a concurrent cognitive task (i.e., dual-task condition). Spatiotemporal gait parameters were measured simultaneously using the pressure-sensing insoles and the electronic walkway. Concurrent validity was assessed by correlation coefficients and Bland-Altman methodology. Test-retest reliability was examined by intraclass correlation coefficients (ICC) and minimal detectable changes (MDC). The validity results showed moderate to excellent correlations and good agreement between the two systems. Concerning test-retest reliability, moderate-to-excellent ICC values and acceptable MDC demonstrated the repeatability of the measured gait parameters. Our findings support the use of these insoles as complementary instruments to conventional tools during single and dual-task conditions.
Collapse
Affiliation(s)
- Monica Parati
- Neuroengineering and Medical Robotics Laboratory, Department of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, Italy
- Istituti Clinici Scientifici Maugeri IRCCS, 20138 Milan, Italy
| | - Matteo Gallotta
- Istituti Clinici Scientifici Maugeri IRCCS, 20138 Milan, Italy
| | - Manuel Muletti
- Istituti Clinici Scientifici Maugeri IRCCS, 20138 Milan, Italy
| | - Annalisa Pirola
- Istituti Clinici Scientifici Maugeri IRCCS, 20138 Milan, Italy
| | - Alice Bellafà
- Istituti Clinici Scientifici Maugeri IRCCS, 20138 Milan, Italy
| | | | - Simona Ferrante
- Neuroengineering and Medical Robotics Laboratory, Department of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, Italy
| |
Collapse
|
9
|
Bruni F, Borghesi F, Mancuso V, Riva G, Stramba-Badiale M, Pedroli E, Cipresso P. Cognition Meets Gait: Where and How Mind and Body Weave Each Other in a Computational Psychometrics Approach in Aging. Front Aging Neurosci 2022; 14:909029. [PMID: 35875804 PMCID: PMC9304933 DOI: 10.3389/fnagi.2022.909029] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 06/16/2022] [Indexed: 11/26/2022] Open
Abstract
Aging may be associated with conditions characterized by motor and cognitive alterations, which could have a detrimental impact on daily life. Although motors and cognitive aspects have always been treated as separate entities, recent literature highlights their relationship, stressing a strong association between locomotion and executive functions. Thus, designing interventions targeting the risks deriving from both components’ impairments is crucial: the dual-task represents a starting point. Although its role in targeting and decreasing difficulties in aging is well known, most interventions are focused on a single domain, proposing a vertical model in which patients emerge only for a single aspect per time during assessment and rehabilitation. In this perspective, we propose a view of the individual as a whole between mind and body, suggesting a multicomponent and multidomain approach that could integrate different domains at the same time retracing lifelike situations. Virtual Reality, thanks to the possibility to develop daily environments with engaging challenges for patients, as well as to manage different devices to collect multiple data, provides the optimal scenario in which the integration could occur. Artificial Intelligence, otherwise, offers the best methodologies to integrate a great amount of various data to create a predictive model and identify appropriate and individualized interventions. Based on these assumptions the present perspective aims to propose the development of a new approach to an integrated, multimethod, multidimensional training in order to enhance cognition and physical aspects based on behavioral data, incorporating consolidated technologies in an innovative approach to neurology.
Collapse
Affiliation(s)
| | - Francesca Borghesi
- Applied Technology for Neuropsychology Lab, IRCCS Istituto Auxologico Italiano, Milan, Italy
| | | | - Giuseppe Riva
- Applied Technology for Neuropsychology Lab, IRCCS Istituto Auxologico Italiano, Milan, Italy
- Human Technology Lab, Catholic University of the Sacred Heart, Milan, Italy
| | - Marco Stramba-Badiale
- Department of Geriatrics and Cardiovascular Medicine, IRCCS Istituto Auxologico Italiano, Milan, Italy
| | - Elisa Pedroli
- Faculty of Psychology, eCampus University, Novedrate, Italy
- Applied Technology for Neuropsychology Lab, IRCCS Istituto Auxologico Italiano, Milan, Italy
| | - Pietro Cipresso
- Applied Technology for Neuropsychology Lab, IRCCS Istituto Auxologico Italiano, Milan, Italy
- Department of Psychology, University of Turin, Turin, Italy
- *Correspondence: Pietro Cipresso,
| |
Collapse
|
10
|
Zhong R, Gao T. Impact of walking states, self-reported daily walking amount and age on the gait of older adults measured with a smart-phone app: a pilot study. BMC Geriatr 2022; 22:259. [PMID: 35351019 PMCID: PMC8961264 DOI: 10.1186/s12877-022-02947-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2021] [Accepted: 03/16/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Smartphones provide a cost-effective avenue for gait assessment among older adults in the community. The purpose of this study is to explore the impact of walking state, self-reported daily walking amount, and age on gait quality, using a smartphone application. METHODS One hundred older adult individuals from North China, aged 73.0 ± 7.7 years, voluntarily participated in this study. They performed three walking tests: normal walking, fast walking, and visually impaired walking. Three-dimensional acceleration data for gait were obtained using the smartphone app Pocket Gait. This study used multivariate analysis of variance (MANOVA) to explore the effects of the walking state, self-reported daily walking amount, and age on the step frequency, root mean square (RMS) acceleration, step time variability, regularity, and symmetry. RESULTS The walking state, self-reported daily walking amount, and age had statistically significant effects on gait quality. Compared with normal walking, the step frequency, RMS acceleration, variability, and regularity were greater in the fast-walking state, and simulated visually impaired walking did not significantly affect gait quality. Relatively older individuals had a significant decline in gait quality compared to (relatively) younger older adult individuals. Compared with older adults who walked less than 1 km a day, older adults who walked more had better gait quality. CONCLUSIONS The walking state, self-reported daily walking amount, and age have a significant effect on the gait quality of older adults. Walking with pigmented sunglasses can be used as a training intervention to improve gait performance. Older adult people who walk less than 1 km/day have worse gait quality compared with their counterparts.
Collapse
Affiliation(s)
- Runting Zhong
- School of Business, Jiangnan University, Wuxi, Jiangsu, 214122, PR China.
| | - Tian Gao
- School of Business, Jiangnan University, Wuxi, Jiangsu, 214122, PR China
| |
Collapse
|
11
|
Roth N, Wieland GP, Kuderle A, Ullrich M, Gladow T, Marxreiter F, Klucken J, Eskofier BM, Kluge F. Do We Walk Differently at Home? A Context-Aware Gait Analysis System in Continuous Real-World Environments. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:1932-1935. [PMID: 34891665 DOI: 10.1109/embc46164.2021.9630378] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Driven by the advancements of wearable sensors and signal processing algorithms, studies on continuous real-world monitoring are of major interest in the field of clinical gait and motion analysis. While real-world studies enable a more detailed and realistic insight into various mobility parameters such as walking speed, confounding and environmental factors might skew those digital mobility outcomes (DMOs), making the interpretation of results challenging. To consider confounding factors, context information needs to be included in the analysis. In this work, we present a context-aware mobile gait analysis system that can distinguish between gait recorded at home and not at home based on Bluetooth proximity information. The system was evaluated on 9 healthy subjects and 6 Parkinsons disease (PD) patients. The classification of the at home/not at home context reached an average F1-score of 98.2 ± 3.2 %. A context-aware analysis of gait parameters revealed different walking bout length distributions between the two environmental conditions. Furthermore, a reduction of gait speed within the at home context compared to walking not at home of 8.9 ± 9.4 % and 8.7 ±5.9 % on average for healthy and PD subjects was found, respectively. Our results indicate the influence of the recording environment on DMOs and, therefore, emphasize the importance of context in the analysis of continuous motion data. Hence, the presented work contributes to a better understanding of confounding factors for future real-world studies.
Collapse
|
12
|
Jacobs D, Farid L, Ferré S, Herraez K, Gracies JM, Hutin E. Evaluation of the Validity and Reliability of Connected Insoles to Measure Gait Parameters in Healthy Adults. SENSORS 2021; 21:s21196543. [PMID: 34640868 PMCID: PMC8512009 DOI: 10.3390/s21196543] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 09/21/2021] [Accepted: 09/23/2021] [Indexed: 11/16/2022]
Abstract
The continuous, accurate and reliable estimation of gait parameters as a measure of mobility is essential to assess the loss of functional capacity related to the progression of disease. Connected insoles are suitable wearable devices which allow precise, continuous, remote and passive gait assessment. The data of 25 healthy volunteers aged 20 to 77 years were analysed in the study to validate gait parameters (stride length, velocity, stance, swing, step and single support durations and cadence) measured by FeetMe® insoles against the GAITRite® mat reference. The mean values and the values of variability were calculated per subject for GAITRite® and insoles. A t-test and Levene’s test were used to compare the gait parameters for means and variances, respectively, obtained for both devices. Additionally, measures of bias, standard deviation of differences, Pearson’s correlation and intraclass correlation were analysed to explore overall agreement between the two devices. No significant differences in mean and variance between the two devices were detected. Pearson’s correlation coefficients of averaged gait estimates were higher than 0.98 and 0.8, respectively, for unipedal and bipedal gait parameters, supporting a high level of agreement between the two devices. The connected insoles are therefore a device equivalent to GAITRite® to estimate the mean and variability of gait parameters.
Collapse
Affiliation(s)
- Damien Jacobs
- FeetMe S.A.S., 157 bd. MacDonald, 75019 Paris, France; (L.F.); (S.F.)
- Correspondence:
| | - Leila Farid
- FeetMe S.A.S., 157 bd. MacDonald, 75019 Paris, France; (L.F.); (S.F.)
| | - Sabine Ferré
- FeetMe S.A.S., 157 bd. MacDonald, 75019 Paris, France; (L.F.); (S.F.)
| | - Kilian Herraez
- UFR de Mathématiques, Université Pierre et Marie Curie, 75005 Paris, France;
| | - Jean-Michel Gracies
- Laboratoire Analyse et Restauration du Mouvement (ARM), Hôpitaux Universitaires Henri Mondor, Assistance Publique des Hôpitaux de Paris (AP-HP), 94000 Créteil, France; (J.-M.G.); (E.H.)
- EA 7377 Bioingénierie, Tissus et Neuroplasticité (BIOTN), Université Paris-Est Créteil (UPEC), 94000 Créteil, France
| | - Emilie Hutin
- Laboratoire Analyse et Restauration du Mouvement (ARM), Hôpitaux Universitaires Henri Mondor, Assistance Publique des Hôpitaux de Paris (AP-HP), 94000 Créteil, France; (J.-M.G.); (E.H.)
- EA 7377 Bioingénierie, Tissus et Neuroplasticité (BIOTN), Université Paris-Est Créteil (UPEC), 94000 Créteil, France
| |
Collapse
|